Mathematical Theory of Subdivision: Finite Element and Wavelet Methods, Sandeep Kumar, Ashish Pathak, Debashis Khan
Автор: Amir Z. Averbuch; Pekka Neittaanmaki; Valery A. Zh Название: Spline and Spline Wavelet Methods with Applications to Signal and Image Processing ISBN: 9401789258 ISBN-13(EAN): 9789401789257 Издательство: Springer Рейтинг: Цена: 156720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume provides universal methodologies accompanied by Matlab software to manipulate numerous signal and image processing applications. SHA reduces the design of different spline types such as splines, spline wavelets (SW), wavelet frames (SWF) and wavelet packets (SWP) and their manipulations by simple operations.
Автор: Sabrine Arfaoui, Imen Rezgui, Anouar Ben Mabrouk Название: Wavelet Analysis on the Sphere: Spheroidal Wavelets ISBN: 311048109X ISBN-13(EAN): 9783110481099 Издательство: Walter de Gruyter Рейтинг: Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This monograph is concerned with wavelet harmonic analysis on the sphere. By starting with orthogonal polynomials and functional Hilbert spaces on the sphere, the foundations are laid for the study of spherical harmonics such as zonal functions. The book also discusses the construction of wavelet bases using special functions, especially Bessel, Hermite, Tchebychev, and Gegenbauer polynomials.
Contents Review of orthogonal polynomials Homogenous polynomials and spherical harmonics Review of special functions Spheroidal-type wavelets Some applications Some applications
Автор: Addison Название: The Illustrated Wavelet Transform H ISBN: 1482251329 ISBN-13(EAN): 9781482251326 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance has been fully updated and revised to reflect recent developments in the theory and practical applications of wavelet transform methods. The book is designed specifically for the applied reader in science, engineering, medicine and finance. Newcomers to the subject will find an accessible and clear account of the theory of continuous and discrete wavelet transforms, while readers already acquainted with wavelets can use the book to broaden their perspective. One of the many strengths of the book is its use of several hundred illustrations, some in colour, to convey key concepts and their varied practical uses. Chapters exploring these practical applications highlight both the similarities and differences in wavelet transform methods across different disciplines and also provide a comprehensive list of over 1000 references that will serve as a valuable resource for further study. Paul Addison is a Technical Fellow with Medtronic, a global medical technology company. Previously, he was co-founder and CEO of start-up company, CardioDigital Ltd (and later co-founded its US subsidiary, CardioDigital Inc) - a company concerned with the development of novel wavelet-based methods for biosignal analysis. He has a master’s degree in engineering and a PhD in fluid mechanics, both from the University of Glasgow, Scotland (founded 1451). His former academic life as a tenured professor of fluids engineering included the output of a large number of technical papers, covering many aspects of engineering and bioengineering, and two textbooks: Fractals and Chaos: An Illustrated Course and the first edition of The Illustrated Wavelet Transform Handbook. At the time of publication, the author has over 100 issued US patents concerning a wide range of medical device technologies, many of these concerning the wavelet transform analysis of biosignals. He is both a Chartered Engineer and Chartered Physicist.
"This book is suitable as a textbook for an introductory undergraduate mathematics course on discrete Fourier and wavelet transforms for students with background in calculus and linear algebra. The particular strength of this book is its accessibility to students with no background in analysis. The exercises and computer explorations provide the reader with many opportunities for active learning. Studying from this text will also help students strengthen their background in linear algebra."
Mathematical Association of America
This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.
It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.
"This book is suitable as a textbook for an introductory undergraduate mathematics course on discrete Fourier and wavelet transforms for students with background in calculus and linear algebra. The particular strength of this book is its accessibility to students with no background in analysis. The exercises and computer explorations provide the reader with many opportunities for active learning. Studying from this text will also help students strengthen their background in linear algebra."
Mathematical Association of America
This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.
It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.
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